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Autoscaling the Compute Resource of a PerconaXtraDB Cluster Database
This guide will show you how to use KubeDB to autoscale compute resources i.e. cpu and memory of a PerconaXtraDB replicaset database.
Before You Begin
At first, you need to have a Kubernetes cluster, and the
kubectlcommand-line tool must be configured to communicate with your cluster.Install
KubeDBCommunity, Ops-Manager and Autoscaler operator in your cluster following the steps here.Install
Metrics Serverfrom hereYou should be familiar with the following
KubeDBconcepts:
To keep everything isolated, we are going to use a separate namespace called demo throughout this tutorial.
$ kubectl create ns demo
namespace/demo created
Autoscaling of Cluster Database
Here, we are going to deploy a PerconaXtraDB Cluster using a supported version by KubeDB operator. Then we are going to apply PerconaXtraDBAutoscaler to set up autoscaling.
Deploy PerconaXtraDB Cluster
In this section, we are going to deploy a PerconaXtraDB Cluster with version 8.0.26. Then, in the next section we will set up autoscaling for this database using PerconaXtraDBAutoscaler CRD. Below is the YAML of the PerconaXtraDB CR that we are going to create,
If you want to autoscale PerconaXtraDB
Standalone, Just remove thespec.Replicasfrom the below yaml and rest of the steps are same.
apiVersion: kubedb.com/v1
kind: PerconaXtraDB
metadata:
name: sample-pxc
namespace: demo
spec:
version: "8.0.26"
replicas: 3
storageType: Durable
storage:
storageClassName: "standard"
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 1Gi
podTemplate:
spec:
containers:
- name: perconaxtradb
resources:
requests:
cpu: "200m"
memory: "300Mi"
limits:
cpu: "200m"
memory: "300Mi"
deletionPolicy: WipeOut
Let’s create the PerconaXtraDB CRO we have shown above,
$ kubectl create -f https://github.com/kubedb/docs/raw/v2024.11.18/docs/guides/percona-xtradb/autoscaler/compute/cluster/examples/sample-pxc.yaml
perconaxtradb.kubedb.com/sample-pxc created
Now, wait until sample-pxc has status Ready. i.e,
$ kubectl get perconaxtradb -n demo
NAME VERSION STATUS AGE
sample-pxc 8.0.26 Ready 14m
Let’s check the Pod containers resources,
$ kubectl get pod -n demo sample-pxc-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "200m",
"memory": "300Mi"
},
"requests": {
"cpu": "200m",
"memory": "300Mi"
}
}
Let’s check the PerconaXtraDB resources,
$ kubectl get perconaxtradb -n demo sample-pxc -o json | jq '.spec.podTemplate.spec.containers[] | select(.name == "perconaxtradb") | .resources'
{
"limits": {
"cpu": "200m",
"memory": "300Mi"
},
"requests": {
"cpu": "200m",
"memory": "300Mi"
}
}
You can see from the above outputs that the resources are same as the one we have assigned while deploying the perconaxtradb.
We are now ready to apply the PerconaXtraDBAutoscaler CRO to set up autoscaling for this database.
Compute Resource Autoscaling
Here, we are going to set up compute resource autoscaling using a PerconaXtraDBAutoscaler Object.
Create PerconaXtraDBAutoscaler Object
In order to set up compute resource autoscaling for this database cluster, we have to create a PerconaXtraDBAutoscaler CRO with our desired configuration. Below is the YAML of the PerconaXtraDBAutoscaler object that we are going to create,
apiVersion: autoscaling.kubedb.com/v1alpha1
kind: PerconaXtraDBAutoscaler
metadata:
name: px-as-compute
namespace: demo
spec:
databaseRef:
name: sample-pxc
opsRequestOptions:
timeout: 3m
apply: IfReady
compute:
perconaxtradb:
trigger: "On"
podLifeTimeThreshold: 5m
resourceDiffPercentage: 20
minAllowed:
cpu: 250m
memory: 400Mi
maxAllowed:
cpu: 1
memory: 1Gi
containerControlledValues: "RequestsAndLimits"
controlledResources: ["cpu", "memory"]
Here,
spec.databaseRef.namespecifies that we are performing compute resource scaling operation onsample-pxcdatabase.spec.compute.perconaxtradb.triggerspecifies that compute autoscaling is enabled for this database.spec.compute.perconaxtradb.podLifeTimeThresholdspecifies the minimum lifetime for at least one of the pod to initiate a vertical scaling.spec.compute.perconaxtradb.resourceDiffPercentagespecifies the minimum resource difference in percentage. The default is 10%. If the difference between current & recommended resource is less than ResourceDiffPercentage, Autoscaler Operator will ignore the updating.spec.compute.perconaxtradb.minAllowedspecifies the minimum allowed resources for the database.spec.compute.perconaxtradb.maxAllowedspecifies the maximum allowed resources for the database.spec.compute.perconaxtradb.controlledResourcesspecifies the resources that are controlled by the autoscaler.spec.compute.perconaxtradb.containerControlledValuesspecifies which resource values should be controlled. The default is “RequestsAndLimits”.spec.opsRequestOptions.applyhas two supported value :IfReady&Always. UseIfReadyif you want to process the opsReq only when the database is Ready. And useAlwaysif you want to process the execution of opsReq irrespective of the Database state.spec.opsRequestOptions.timeoutspecifies the maximum time for each step of the opsRequest(in seconds). If a step doesn’t finish within the specified timeout, the ops request will result in failure.
Let’s create the PerconaXtraDBAutoscaler CR we have shown above,
$ kubectl apply -f https://github.com/kubedb/docs/raw/v2024.11.18/docs/guides/percona-xtradb/autoscaler/compute/cluster/examples/pxas-compute.yaml
perconaxtradbautoscaler.autoscaling.kubedb.com/pxas-compute created
Verify Autoscaling is set up successfully
Let’s check that the perconaxtradbautoscaler resource is created successfully,
$ kubectl get perconaxtradbautoscaler -n demo
NAME AGE
px-as-compute 5m56s
$ kubectl describe perconaxtradbautoscaler px-as-compute -n demo
Name: px-as-compute
Namespace: demo
Labels: <none>
Annotations: <none>
API Version: autoscaling.kubedb.com/v1alpha1
Kind: PerconaXtraDBAutoscaler
Metadata:
Creation Timestamp: 2022-09-16T11:26:58Z
Generation: 1
Managed Fields:
...
Resource Version: 846645
UID: 44bd46c3-bbc5-4c4a-aff4-00c7f84c6f58
Spec:
Compute:
Mariadb:
Container Controlled Values: RequestsAndLimits
Controlled Resources:
cpu
memory
Max Allowed:
Cpu: 1
Memory: 1Gi
Min Allowed:
Cpu: 250m
Memory: 400Mi
Pod Life Time Threshold: 5m0s
Resource Diff Percentage: 20
Trigger: On
Database Ref:
Name: sample-pxc
Ops Request Options:
Apply: IfReady
Timeout: 3m0s
Status:
Checkpoints:
Cpu Histogram:
Bucket Weights:
Index: 0
Weight: 10000
Index: 46
Weight: 555
Reference Timestamp: 2022-09-16T00:00:00Z
Total Weight: 2.648440345821337
First Sample Start: 2022-09-16T11:26:48Z
Last Sample Start: 2022-09-16T11:32:52Z
Last Update Time: 2022-09-16T11:33:02Z
Memory Histogram:
Bucket Weights:
Index: 1
Weight: 10000
Reference Timestamp: 2022-09-17T00:00:00Z
Total Weight: 1.391848625060675
Ref:
Container Name: px-coordinator
Vpa Object Name: sample-pxc
Total Samples Count: 19
Version: v3
Cpu Histogram:
Bucket Weights:
Index: 0
Weight: 10000
Index: 3
Weight: 556
Reference Timestamp: 2022-09-16T00:00:00Z
Total Weight: 2.648440345821337
First Sample Start: 2022-09-16T11:26:48Z
Last Sample Start: 2022-09-16T11:32:52Z
Last Update Time: 2022-09-16T11:33:02Z
Memory Histogram:
Reference Timestamp: 2022-09-17T00:00:00Z
Ref:
Container Name: perconaxtradb
Vpa Object Name: sample-pxc
Total Samples Count: 19
Version: v3
Conditions:
Last Transition Time: 2022-09-16T11:27:07Z
Message: Successfully created mariaDBOpsRequest demo/pxops-sample-pxc-6xc1kc
Observed Generation: 1
Reason: CreateOpsRequest
Status: True
Type: CreateOpsRequest
Vpas:
Conditions:
Last Transition Time: 2022-09-16T11:27:02Z
Status: True
Type: RecommendationProvided
Recommendation:
Container Recommendations:
Container Name: perconaxtradb
Lower Bound:
Cpu: 250m
Memory: 400Mi
Target:
Cpu: 250m
Memory: 400Mi
Uncapped Target:
Cpu: 25m
Memory: 262144k
Upper Bound:
Cpu: 1
Memory: 1Gi
Vpa Name: sample-pxc
Events: <none>
So, the perconaxtradbautoscaler resource is created successfully.
We can verify from the above output that status.vpas contains the RecommendationProvided condition to true. And in the same time, status.vpas.recommendation.containerRecommendations contain the actual generated recommendation.
Our autoscaler operator continuously watches the recommendation generated and creates an perconaxtradbopsrequest based on the recommendations, if the database pod resources are needed to scaled up or down.
Let’s watch the perconaxtradbopsrequest in the demo namespace to see if any perconaxtradbopsrequest object is created. After some time you’ll see that a perconaxtradbopsrequest will be created based on the recommendation.
$ kubectl get perconaxtradbopsrequest -n demo
NAME TYPE STATUS AGE
pxops-sample-pxc-6xc1kc VerticalScaling Progressing 7s
Let’s wait for the ops request to become successful.
$ kubectl get perconaxtradbopsrequest -n demo
NAME TYPE STATUS AGE
pxops-vpa-sample-pxc-z43wc8 VerticalScaling Successful 3m32s
We can see from the above output that the PerconaXtraDBOpsRequest has succeeded. If we describe the PerconaXtraDBOpsRequest we will get an overview of the steps that were followed to scale the database.
$ kubectl describe perconaxtradbopsrequest -n demo pxops-vpa-sample-pxc-z43wc8
Name: pxops-sample-pxc-6xc1kc
Namespace: demo
Labels: <none>
Annotations: <none>
API Version: ops.kubedb.com/v1alpha1
Kind: PerconaXtraDBOpsRequest
Metadata:
Creation Timestamp: 2022-09-16T11:27:07Z
Generation: 1
Managed Fields:
API Version: ops.kubedb.com/v1alpha1
Fields Type: FieldsV1
fieldsV1:
f:metadata:
f:ownerReferences:
.:
k:{"uid":"44bd46c3-bbc5-4c4a-aff4-00c7f84c6f58"}:
f:spec:
.:
f:apply:
f:databaseRef:
.:
f:name:
f:timeout:
f:type:
f:verticalScaling:
.:
f:perconaxtradb:
.:
f:limits:
.:
f:cpu:
f:memory:
f:requests:
.:
f:cpu:
f:memory:
Manager: kubedb-autoscaler
Operation: Update
Time: 2022-09-16T11:27:07Z
API Version: ops.kubedb.com/v1alpha1
Fields Type: FieldsV1
fieldsV1:
f:status:
.:
f:conditions:
f:observedGeneration:
f:phase:
Manager: kubedb-ops-manager
Operation: Update
Subresource: status
Time: 2022-09-16T11:27:07Z
Owner References:
API Version: autoscaling.kubedb.com/v1alpha1
Block Owner Deletion: true
Controller: true
Kind: PerconaXtraDBAutoscaler
Name: px-as-compute
UID: 44bd46c3-bbc5-4c4a-aff4-00c7f84c6f58
Resource Version: 846324
UID: c2b30107-c6d3-44bb-adf3-135edc5d615b
Spec:
Apply: IfReady
Database Ref:
Name: sample-pxc
Timeout: 2m0s
Type: VerticalScaling
Vertical Scaling:
Mariadb:
Limits:
Cpu: 250m
Memory: 400Mi
Requests:
Cpu: 250m
Memory: 400Mi
Status:
Conditions:
Last Transition Time: 2022-09-16T11:27:07Z
Message: Controller has started to Progress the PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
Observed Generation: 1
Reason: OpsRequestProgressingStarted
Status: True
Type: Progressing
Last Transition Time: 2022-09-16T11:30:42Z
Message: Successfully restarted PerconaXtraDB pods for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
Observed Generation: 1
Reason: SuccessfullyRestatedPetSet
Status: True
Type: RestartPetSet
Last Transition Time: 2022-09-16T11:30:47Z
Message: Vertical scale successful for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
Observed Generation: 1
Reason: SuccessfullyPerformedVerticalScaling
Status: True
Type: VerticalScaling
Last Transition Time: 2022-09-16T11:30:47Z
Message: Controller has successfully scaled the PerconaXtraDB demo/pxops-sample-pxc-6xc1kc
Observed Generation: 1
Reason: OpsRequestProcessedSuccessfully
Status: True
Type: Successful
Observed Generation: 1
Phase: Successful
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Starting 8m48s KubeDB Enterprise Operator Start processing for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
Normal Starting 8m48s KubeDB Enterprise Operator Pausing PerconaXtraDB databse: demo/sample-pxc
Normal Successful 8m48s KubeDB Enterprise Operator Successfully paused PerconaXtraDB database: demo/sample-pxc for PerconaXtraDBOpsRequest: pxops-sample-pxc-6xc1kc
Normal Starting 8m43s KubeDB Enterprise Operator Restarting Pod: demo/sample-pxc-0
Normal Starting 7m33s KubeDB Enterprise Operator Restarting Pod: demo/sample-pxc-1
Normal Starting 6m23s KubeDB Enterprise Operator Restarting Pod: demo/sample-pxc-2
Normal Successful 5m13s KubeDB Enterprise Operator Successfully restarted PerconaXtraDB pods for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
Normal Successful 5m8s KubeDB Enterprise Operator Vertical scale successful for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
Normal Starting 5m8s KubeDB Enterprise Operator Resuming PerconaXtraDB database: demo/sample-pxc
Normal Successful 5m8s KubeDB Enterprise Operator Successfully resumed PerconaXtraDB database: demo/sample-pxc
Normal Successful 5m8s KubeDB Enterprise Operator Controller has Successfully scaled the PerconaXtraDB database: demo/sample-pxc
Now, we are going to verify from the Pod, and the PerconaXtraDB yaml whether the resources of the replicaset database has updated to meet up the desired state, Let’s check,
$ kubectl get pod -n demo sample-pxc-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "250m",
"memory": "400Mi"
},
"requests": {
"cpu": "250m",
"memory": "400Mi"
}
}
$ kubectl get perconaxtradb -n demo sample-pxc -o json | jq '.spec.podTemplate.spec.containers[] | select(.name == "perconaxtradb") | .resources'
{
"limits": {
"cpu": "250m",
"memory": "400Mi"
},
"requests": {
"cpu": "250m",
"memory": "400Mi"
}
}
The above output verifies that we have successfully autoscaled the resources of the PerconaXtraDB replicaset database.
Cleaning Up
To clean up the Kubernetes resources created by this tutorial, run:
kubectl delete perconaxtradb -n demo sample-pxc
kubectl delete perconaxtradbautoscaler -n demo px-as-compute
kubectl delete ns demo